Alzheimers disease (AD) is one of the most common causes of dementia and frailty. This study aimed to use bioinformatics analysis to identify differentially expressed genes (DEGs) in AD. The Expression profiling by high throughput sequencing dataset GSE125583 was downloaded from the Gene Expression Omnibus (GEO) database and DEGs were identified. After assessment of Gene Ontology (GO) terms and pathway enrichment for DEGs, a protein protein interaction (PPI) network, module analysis, miRNA hub gene regulatory network construction and TF hub gene regulatory network were conducted via comprehensive target prediction and network analyses. Finally, we validated hub genes by receiver operating characteristic curve (ROC) and RT-PCR. In total, 956 DEGs were identified in the AD samples, including 479 up regulated genes and 477 down regulated genes. Functional enrichment analysis showed that these DEGs are mainly involved in the neuronal system, GPCR ligand binding, regulation of biological quality and cell communication. The hub genes of PAK1, ELAVL2, NSF, HTR2C, TERT, UBD, MKI67, HSPB1, PYHIN1 and TES might be associated with AD. The diagnostic value and expression levels of these hub genes in AD were further confirmed by ROC analysis and RT-PCR. In conclusion, we identified pathways and crucial candidate genes that affect the outcomes of patients with AD, and these genes might serve as potential therapeutic targets.
Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis and RT-PCR confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.
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